Smart location determination

ABSTRACT

In one example in accordance with the present disclosure, a system for smart location determination includes a session information accessor to access session information that details a session of a user system as it connects to a web technology server. The system includes a knowledge base that includes known common session information of multiple geographic locations. The system includes a session information comparator to compare the accessed session information to the knowledge base, and based on the comparison, determine a geographic location of the user system or verify an alleged geographic location.

BACKGROUND

It may be desirable or required for a web technology (e.g., a webpage,web application, mobile application, etc.) to determine the location(e.g., geographic location, nationality, etc.) of a user (i.e., enduser) of the web technology. For example, a content publisher or agovernment may impose a legal restriction on particular users (e.g.,users outside of a particular country) accessing particular content(sometimes referred to as Geo Blocking). As another example, some webtechnologies offer tailored content or advertisements to users based onthe location of the user.

BRIEF DESCRIPTION OF THE DRAWINGS

The following detailed description references the drawings, wherein:

FIG. 1 is a block diagram of an example computing environment in whichsmart location determination may be useful;

FIG. 2 is a flowchart of an example method for smart locationdetermination;

FIG. 3 is a block diagram of an example system for smart locationdetermination;

FIG. 4 is a flowchart of an example method for smart locationdetermination; and

FIG. 5 is a block diagram of an example system for smart locationdetermination.

DETAILED DESCRIPTION

As explained above, it may be desirable or required for a web technology(e.g., a webpage, web application, mobile application, etc.) todetermine the location (e.g., geographic location, nationality, etc.) ofa user (i.e., end user) of the web technology. In some situations, thelocation of a user may be determined based on the IP (internet protocol)address of the user's device or by analyzing other aspects of the user'snetwork connection. Such methods of determining user location may beinaccurate because, among other reasons, a user may “spoof” (i.e.,falsely fabricate) or hide their IP address. For example, tools such asVPNs (virtual private network) and proxy servers allow users to routetheir connection through an intermediary before connecting to an enddestination. The numbers of users that employ such tools is on asignificant rise. Thus, various methods of determining a user's locationare becoming less and less accurate.

The present disclosure describes smart location determination. Thepresent disclosure describes determining a location (e.g., geographiclocation) of a user system, wherein the location may be determined withaccuracy despite a spoofed or hidden IP address. The present disclosuredescribes comparing session information (that details a session of theuser system as it sends a request to a web technology server) to knownsession information of multiple geographic locations. Based on thecomparison, a “real” or spoof-proof location of the user system may bedetermined or an alleged location (e.g., from an alleged IP address) maybe verified.

FIG. 1 is a block diagram of an example computing environment 100 inwhich smart location determination may be useful. Computing environment100 may include a user system 102, a web technology system 110 and asmart system 120. User system 120 may communicate (e.g., over a network)with web technology system 110, for example, to access a web technology.Web technology system 110 may host the web technology for various usersystems (e.g., 102) and may extract session information that detailssessions of user systems (e.g., 102) as they connect to the webtechnology. For a particular connection between a user system (e.g.,102) and the web technology, web technology system 110 may send (e.g.,over a network) certain session information (e.g., 111) to smart system120. Smart system 120 may analyze the session information to determine ageographic location of the user system (e.g., 102) or to verify analleged geographic location (e.g., one indicated by the user system's IPaddress). The above mentioned networks, which in some examples may bethe same network, may each be any wired or wireless network, and mayinclude any number of hubs, routers, switches, cell towers or the like.Such networks may each be, for example, part of a cellular network, partof the internet, part of an intranet and/or other type of network.

User system 102 may include at least one computing device that iscapable of communicating with at least one remote system (e.g., 110)over a network. User system 102 may include a web technology accessor104. Web technology accessor 104 may access a web technology on a remotesystem (e.g., 110). More specifically, web technology accessor 104 mayissue requests (e.g., HTTP requests) to the remote system and mayreceive data in return that is used to present the web technology on theuser system and allows a user of the user system to interact with theweb technology. In some examples, web technology accessor 104 may be aweb browser, and the web technology (hosted on system 110) may be awebpage. In other examples, web technology accessor 104 may be a mobileapplication, and the web technology may be mobile applicationserver-side code. This disclosure contemplates various other examples ofweb technology accesssors and web technologies.

Web technology system 110 may include at least one computing device thatis capable of communicating with at least one user system (e.g., 102)over a network. The term “system” may be used to refer to a singlecomputing device or multiple computing devices that communicate witheach other (e.g., via a network) and operate together to provide aunified service. Web technology system 110 may store (or “host”) codefor a web technology, for example, an interactive webpage or website, amobile application or the like. Web technology system 110 may receiverequests from user systems (e.g., 102) to interact with the webtechnology, and in response may return data to the user systems. Webtechnology system 110 may include a web technology server 112, a sessioninformation extractor 114 and a smart information analyzer 116. Each ofthese components may each include instructions (e.g., stored on amachine-readable storage medium of system 110) that, when executed(e.g., by a processor of system 110), implement the functionality of thecomponent. Alternatively or in addition, each of these components mayinclude electronic circuitry (i.e., hardware) that implements thefunctionality of the component.

Web technology server 112 may provide or “serve” the web technology torequesting user systems (e.g., 102). Web technology server 112 mayreceive requests from the user systems, may access the code for the webtechnology and may return data to the requesting user systems.

Session information extractor 114 may analyze requests from user systems(e.g., 102) received by the web technology system 110 to access the webtechnology. A particular request may include several pieces ofinformation. For example, a request may include the IP address of therequesting device. As mentioned above, this IP address may in somesituations be spoofed or hidden. The request may also include sessioninformation. The term “session information” may be used throughout thisdisclosure to refer to information that details a session of a usersystem (e.g., 102) as it connects to a web technology server (e.g.,112). Session information may include both system information of theuser system and information about the web technology accessor (e.g., aweb browser). System information may include details about the physical(e.g., hardware) aspects of the user system and software (e.g.,operating system) aspects of the user system. Information about the webtechnology accessor may include details about the version of theaccessor, language of the accessor, plugins running with the accessorand the like. In some examples, the IP address of the requesting devicemay be considered as part of the session information. However, invarious descriptions herein, the IP address may be considered asseparate so that a distinction can be made between the IP address andother session information.

The following description details several examples of pieces of sessioninformation for the purposes of illustrating that session informationcan refer to a broad range of information. Each piece of sessioninformation may also be referred to as a parameter or “sessionparameter.” One example parameter is the request header (e.g., HTTPrequest header), which may include multiple fields, each with a valuablepiece of information about the session. Another example is theAccept-Language header, which includes information about the user'slanguage preferences. Another example is the version of a particularplugin (e.g., Java Applet). Another example is the operating systemversion of the user system. Another example is the version of the webtechnology accessor (e.g., the version of a web browser). In the exampleof web browsers, session information may indicate both a major webbrowser version and a minor web browser version. Another example of asession parameter is the version of particular software running on theuser system, for example, the Flash player version. Another example isdetails about the configuration of the user system, e.g., user screenresolution. Session information may refer to many other types ofinformation, and the descriptions include herein contemplate variousother types of session information.

As one specific example, session information may be extracted from auser agent string. Various web technology accessors (e.g., web browsers,web applicatinos, etc.) may maintain a user agent string to accumulatemany useful pieces of session information in a single place. In someexamples, when a web technology accessor maintains a user agent string,it may send this string as part of the request when the web technologyaccessor (e.g., 104) accesses a web technology (e.g., on system 110).Thus, in some examples, session information extractor 114 may analyze arequest, identify a user agent string included in the request, andfurther analyze the user agent string to extract session information(including multiple session parameters).

Session information extractor 114 may select a number of the availablesession parameters to send to smart system 120. For example, a subset ofthe available session parameters may be determined (e.g., by a developerof the web technology) as important to the location determinations to beperformed by smart system 120. Session information extractor 114 mayalso assign an importance rating to at least one of the selected sessionparameters, and in some examples, to all of the selected sessionparameters. For example, using these importance ratings, a developercould indicate that the “browser language” parameter is very important,while the “operating system language” is less important. Various ratingsscales (e.g., X/10 where X is an integer) maybe used to indicateimportance.

Session information extractor 114 may also assign an importance ratingto the IP address (i.e., the alleged IP address) of the request. Forexample, the developer could indicate that the IP address is notrelevant at all to the location determinations to be made by smartsystem 120.

The session parameters selected by session information extractor 114 mayform a sort of “digital fingerprint” of a particular session. Theimportance ratings of the various parameters may, in some examples, alsobe part of the digital fingerprint. In the present disclosure, thedigital fingerprint does not include the IP address, even though the IPaddress may be sent by the web technology system 110 to smart system120. A digital fingerprint may be a calculated value or code based onselected session parameters. Alternatively, the term digital fingerprintmay just be a term used to refer to the configuration of selectedsession parameters and perhaps their corresponding importance ratings.

Session information extractor 114 may send session information (e.g.,111) for a particular session to smart system 120. Session informationextractor 114 may send all available session parameters or only selectedparameters. Session information extractor 114 may also send importanceratings for at least one of the selected session parameters. Sessioninformation extractor 114 may send raw session parameters or it maycompute a digital signature value or code and send that instead.Likewise, if importance ratings are used, session information extractor114 may send raw session parameters and associated importance ratings orit may compute a digital signature value or code that accounts forimportance ratings and send that instead. Session information extractor114 may also send the IP address (i.e., the alleged IP address) of therequest.

Smart information analyzer 116 may analyze smart information (e.g., 121)that is sent back from smart system 120. As explain in more detailbelow, smart information 121 may include, among other things, a location(e.g., geographic location) related to the particular user session forwhich session information (e.g., 111) was sent to smart system 120. Thislocation may be accurate even if a user of user system 102 has spoofedor hidden their IP address. Thus, this location may be referred to as a“real” or “spoof-proof” location. The web technology system may use thissmart information for various purposes, e.g., in line with desires orrequirements of content publishers or governments. As one example, theweb technology or other program of the web technology system may analyzeand use the smart information in an automated manner. As anotherexample, a developer of the web technology may manually review thereceived information.

Smart system 120 may include at least one computing device that iscapable of communicating with at least one web technology system (e.g.,110) over a network. The term “system” may be used to refer to a singlecomputing device or multiple computing devices that communicate witheach other (e.g., via a network) and operate together to provide aunified service. Smart system 120 may receive session information (e.g.,111) from web technology system 110 and may analyze this information todetermine a “real” location (e.g., geographic location) of the usersystem (e.g., 102) or verify an alleged location (e.g., indicated by anIP address). Smart system 120 may return this “real” location andperhaps other data to the web technology system 110 as indicated bysmart information 121 of FIG. 1. In some examples, smart system 120 maybe a Saas (software as a service) system.

Smart system 120 may include a session information accessor 122, analleged location determinor 124, a session information comparator 126, asimilarity determinor 128 and a smart information presentor 129. Each ofthese components may each include instructions (e.g., stored on amachine-readable storage medium of system 120) that, when executed(e.g., by a processor of system 120), implement the functionality of thecomponent. Alternatively or in addition, each of these components mayinclude electronic circuitry (i.e., hardware) that implements thefunctionality of the component.

Session information accessor 122 may access session information thatdetails a session of a user system (e.g., 102) as it connects to a webtechnology server (e.g., 112). If web technology system 110 is aseparate, remote system from smart system 120, session informationaccessor 122 may receive session information (e.g., 111) from webtechnology system 110, e.g., over a network. In some examples, webtechnology system and smart system 120 may be part of the same system,in which case, session information accessor 122 may access the sessioninformation directly from session information extractor 114. Sessioninformation accessor 122 may also access and/or receive an alleged IPaddress (or allege location based on the IP address) of the user system102.

Alleged location determinor 124 may determine an alleged location (e.g.,geographic location, country, etc.) of user system 102. For example,this may be a location associated with the alleged IP address of usersystem 102. Alleged location determinor 124 may use a look-up table orother database to determine a location associated with the alleged IPaddress. In some examples, web technology system 110 may determine thelocation associated with the alleged IP address, and may send thisalleged location directly to smart system instead of or in conjunctionwith the alleged IP address. As described above, the IP address of usersystem 102 may have been spoofed or hidden, but alleged locationdeterminor 124 may use the alleged IP address and/or associated locationnonetheless. For example, the alleged location may be given some (evenif limited) weight in the process of smart location determination.Additionally or instead, the alleged location may be used to determinewhether the alleged location for a particular request is indeed accurate(and to what degree).

Session information comparator 126 may use the session information (ordigital fingerprint) accessed by session information accessor 122 tocompare to a knowledge base (e.g., 127) to determine a location (e.g.,geographic location) of the user system (e.g., 102) or verify an allegedlocation. Smart system 120 may include a knowledge base 127 thatincludes, for multiple locations or regions, session information that iscommon, typical or average for that particular location/region. In otherwords, knowledge base 127 may maintain a “profile” for eachlocation/region. Knowledge base 127 may be created by harvesting usageor session information from many user systems across manylocations/regions. Session information comparator 126 may then comparethe accessed session information (e.g., from 122) to the profiles in theknowledge base 127.

The following will describe a number of examples with regard toknowledge base 127 and comparing to knowledge base 127. In one example,a profile may be maintained for the country of Hungary. This profile mayinclude a session parameter for the Accept-Language header indicating aHungary language preference. This profile may also include a sessionparameter indicating a specific Java Applet version. This profile mayalso include a session parameter indicating a specific operating systemversion (e.g., Windows Vista 32 bit). This profile may also include asession parameter for a specific browser version (e.g., InternetExplorer 9) and a specific Flash player version (e.g., version X). Thisprofile may specify many more (e.g., hundreds more) parameters that arespecific to users that originate their connection from Hungary. Withthis example Hungary profile in mind, if session information comparator126 receives session information (e.g., for user system 102) and it mostclosely matches the Hungary profile, and yet the alleged IP address ofthe user system indicates an Italy location, it can be concluded thatthe IP address is spoofed. Moreover, the likely “real” location (i.e.,Hungary) of the user system can be determined despite the spoofed IPaddress.

Knowledge base 127 may maintain secondary information for varioussession parameters as well. For example, if for a particular country(e.g., China) there is a most popular browser (e.g., Internet Explorer6) and a secondary browser (e.g., Mozilla), knowledge base 127 may storeeach of these. Then, when session information comparator 126 isattempting to match the received session information to a particularprofile, if the received session information indicates usage of asecondary parameter, a match may still be made with a particularprofile, for example, if various other session parameters matchstrongly. In other words, matching to a secondary parameter may beevidence of a profile match, but weaker evidence than a match to aprimary parameter.

Knowledge base 127 may include or be in communication with at least onephysical storage mechanism (e.g., hard drive, solid state drive, tapdrive or the like) capable of storing information including, forexample, a digital database, a file capable of storing text, media,code, settings, other data or the like, or other type of data store.Knowledge base 127 may also include executable instructions stored on atleast one machine-readable storage medium of system 120 and executed byat least one processor of system 120. Alternatively or in addition,knowledge base 127 may include one or more hardware devices includingelectronic circuitry for implementing the functionality of the knowledgebase (e.g., responding to requests for information, performing lookups,returning data, etc.).

Session information comparator 126 may compare session information tothe knowledge base 127 in various ways for various purposes. Forexample, it may compare in order to verify an alleged location (e.g.,from an alleged IP address). In this example, session informationcomparator 126 may look up the profile of the alleged location from theknowledge base 127 and then compare it to the received sessioninformation. As another example, session information comparator 126 maycompare in order to discover the “real” (spoof-proof) location based onthe received session information. In this example, session informationcomparator 126 may analyze multiple profiles in the knowledge base 127,comparing each to the received session information, with the goal offinding the profile that most closely matches the received sessioninformation (e.g., a country with average usage/session information thatmost resembles the usage/session information of user system 102).

As another example, session information comparator 126 may compare inorder to detect when a proxy is being used. In this example, if afteranalyzing received session information for multiple user systems, it isdetected (based on comparison to the knowledge base) that the usersystems are really from various different locations, and yet they allpresent the same IP address or IP domain, it may be concluded that theIP address or IP domain is a proxy. Known proxies may be stored in smartsystem 120, for example, such that for these IP addresses or domains,the alleged IP address may be removed from consideration when analyzingfuture received session information.

Session information comparator 126 may compare to knowledge base 127 bycomparing raw session parameters (received session information) to rawsession parameters (in knowledge base). Alternatively, sessioninformation comparator 126 may compare a digital fingerprint value orcode (of received session information) to digital fingerprint values orcodes (one for each profile in knowledge base). Whether comparisons areperformed on raw session parameters of calculated digital fingerprintvalues or codes may be a design decision, and web technology system 110,smart system 120 and knowledge base 127 may all abide by the samemethodology.

Session information comparator 126 may use importance ratings specifiedby web technology system 110. As described above, at least one of thesession parameters, and in some examples, all of the selected sessionparameters may include an importance rating when received. Sessioninformation comparator 126 may consider these ratings when comparing toprofiles in knowledge base 127. For example, a session parameter in thereceived session information may not match a corresponding sessionparameter in a profile in knowledge base 127, but if that sessionparameter was assigned an importance rating of zero, then the mismatchmay have no effect on the overall matching.

Similarity determinor 128 may determine similarity ratings associatedwith various comparisons performed by session information comparator126. For example, if session information comparator 126 is comparingreceived session information to a profile associated with an allegedlocation (e.g., from an alleged IP address), similarity determinor 128may determine how close the match is (i.e., the similarity rating). Asanother example, if session information comparator 126 is comparingreceived session information to multiple profiles in the knowledge basedto find a closest match, session information comparator 126 maydetermine how close the match is for the best match or for all theprofile comparisons performed. The similarity rating may take the formof a percentage (e.g., 0% is the worst match possible and 100% is thebest match possible) or some other scale of relatedness. Similaritydeterminor 128 may use the importance ratings of various sessionparameters when calculating the similarity rating. Thus, for example, iftwo corresponding parameters do not match, but the importance rating forthat parameter is 0%, then the mismatch may have no effect on thesimilarity rating.

Smart information presenter 129 may send various pieces of information(collectively referred to as smart information 121) back to the webtechnology system 110 (e.g., to smart information analyzer 116), where,for example, a bundle of smart information 121 may be sent back for eachbundle of session information 111 sent to the smart system 120. Smartinformation 121 may include a “real” (spoof-proof) location associatedwith the sent session information 111. Smart information 121 may includea similarity rating associated with that real location. Smartinformation 121 may include an indication of whether an alleged locationor IP address of user system 102 is real or has been spoofed. Smartinformation 121 may include a similarity rating between the allegedlocation and the real location as determined by session informationcomparator 126. Smart information 121 may also include the allegedlocation of an IP address supplied to the smart system 120 if the smartsystem 120 performs such a determination. In some examples, the allegedlocation associated with a supplied IP address of user system 102 may bedetermined by web technology system 110 and in other examples, theallege location may be determined by smart system 120. Smart information121 may also include an indication of whether an alleged location or IPaddress is associated with a known proxy.

In some examples, session information comparator 126 may determine andsmart information presenter 129 may return multiple matching locationsfor a given bundle of session information. For example, based oncomparisons to knowledge base 127, multiple matching locations may bedetermined, and a similarity rating may be determined for each match.Thus, smart information presenter could, for example, return multiplelocations, each with a similarity rating. Then, the multiple locationscould be ranked from most similar to less similar, for example.

FIG. 2 is a flowchart of an example method 200 for smart locationdetermination. Method 200 may be described below as being executed orperformed by at least one system, for example, system 110 of FIG. 1and/or system 120 of FIG. 1. Other suitable systems and/or computingdevices may be used as well. Method 200 may be implemented in the formof executable instructions stored on at least one machine-readablestorage medium of at least one of the systems and executed by at leastone processor of at least one of the systems. Alternatively or inaddition, method 200 may be implemented in the form of electroniccircuitry (e.g., hardware). In alternate embodiments of the presentdisclosure, one or more steps of method 200 may be executedsubstantially concurrently or in a different order than shown in FIG. 2.In alternate embodiments of the present disclosure, method 200 mayinclude more or less steps than are shown in FIG. 2. In someembodiments, one or more of the steps of method 200 may, at certaintimes, be ongoing and/or may repeat.

Method 200 may start at step 202 and continue to step 204, where a firstsystem (e.g., system 110 of FIG. 1) may receive a request from a usersystem (e.g., 102). At step 206, the first system may extract (e.g., viasession information extractor 114) session information from the request,as described in more detail above. At step 208, either the first systemor a second system may determine an alleged location, e.g., based on analleged IP address associated with the request. At step 210, the secondsystem (e.g., system 120 of FIG. 1), which may be the same as the firstsystem in some examples, may compare (e.g., via session informationcomparator) the extracted session information with known common sessioninformation (e.g., stored in knowledge base 127). At step 212, thesecond system, based on the comparison may determine a “real”(spoof-proof) location, as described in more detail above. At step 214,the second system may determine (e.g., via similarity determinor 128) asimilarity rating between the extracted session information and the reallocation, as described in more detail above. Also at step 214, thesecond system may determine a similarity rating between the extractedsession information and the alleged location. At step 216, the secondsystem may return (e.g., via smart information presenter 129) the reallocation and the similarity rating(s).

Referring again to step 210, as an alternate example or in conjunctionwith step 212, method 200 may proceed to step 218 where the secondsystem may verify the alleged location, as described in more detailabove. At step 220, if the alleged location is not verified, method 200may proceed to step 212. Additionally, at step 220, if the allegedlocation or alleged associated IP address is known to be a proxy, asdescribed above, method 200 may proceed to step 212. At step 220, if thealleged location is verified, method 200 may proceed to step 222 wherethe second system may determine (e.g., via similarity determinor 128) asimilarity rating between the extracted session information and thealleged location. At step 224, the second system may return (e.g., viasmart information presenter 129) an indication of the verification (ofthe alleged location) and the associated similarity rating. Method 200may eventually continue to step 226, where method 200 may stop.

FIG. 3 is a block diagram of an example system 300 for smart locationdetermination. System 300 may include at least one computing device thatis capable of communicating with at least one remote system. System 300may be similar to system 120 of FIG. 1, for example. In the embodimentof FIG. 3, system 300 includes a session information accessor 310, aknowledge base 320 and a session information comparator 330. Sessioninformation accessor 310 may be similar to session information accessor122, for example. Session information accessor 310 may access sessioninformation that details a session of a user system (e.g., 102) as itconnects to a web technology server (e.g., 112). Session informationaccessor 310 may be implemented in the form of executable instructionsstored on at least one machine-readable storage medium of system 300 andexecuted by at least one processor of system 300. Alternatively or inaddition, session information accessor 310 may be implemented in theform of one or more hardware devices including electronic circuitry forimplementing the functionality of session information accessor 310.

Knowledge base 320 may be similar to knowledge base 127, for example.Knowledge base 320 may include known common session information ofmultiple geographic locations. Knowledge base 320 may be a data storethat may store digital information. Knowledge base 320 may include or bein communication with at least one physical storage mechanism (e.g.,hard drive, solid state drive, tap drive or the like) capable of storinginformation including, for example, a digital database, a file capableof storing text, media, code, settings, other data or the like, or othertype of data store. Knowledge base 320 may also include executableinstructions stored on at least one machine-readable storage medium ofsystem 300 and executed by at least one processor of system 300.Alternatively or in addition, knowledge base 320 may include one or morehardware devices including electronic circuitry for implementing thefunctionality of the knowledge base (e.g., responding to requests forinformation, performing lookups, returning data, etc.).

Session information comparator 330 may be similar to session informationcomparator 126, for example. Session information comparator 330 maycompare the accessed session information to the knowledge base, andbased on the comparison, determine a geographic location of the usersystem or verify an alleged geographic location. Session informationcomparator 330 may be implemented in the form of executable instructionsstored on at least one machine-readable storage medium of system 300 andexecuted by at least one processor of system 300. Alternatively or inaddition, session information comparator 330 may be implemented in theform of one or more hardware devices including electronic circuitry forimplementing the functionality of session information comparator 330.

FIG. 4 is a flowchart of an example method 400 for smart locationdetermination. Method 400 may be described below as being executed orperformed by a system, for example, system 110 of FIG. 1. Other suitablesystems and/or computing devices may be used as well. Method 400 may beimplemented in the form of executable instructions stored on at leastone machine-readable storage medium of the system and executed by atleast one processor of the system. Alternatively or in addition, method400 may be implemented in the form of electronic circuitry (e.g.,hardware). In alternate embodiments of the present disclosure, one ormore steps of method 400 may be executed substantially concurrently orin a different order than shown in FIG. 4. In alternate embodiments ofthe present disclosure, method 400 may include more or less steps thanare shown in FIG. 4. In some embodiments, one or more of the steps ofmethod 400 may, at certain times, be ongoing and/or may repeat.

Method 400 may start at step 402 and continue to step 404, where thesystem may receive a request from a user system to access a webtechnology. At step 406, the system may extract session information fromthe request that details a session of the user system as it sends therequest. At step 408, the system may send the session information to asmart system to compare the session information to known common sessioninformation of multiple geographic locations. At step 410, the systemmay receive, from the smart system, based on the comparison, ageographic location of the user system or a verification of an allegedgeographic location. Method 400 may eventually continue to step 412,where method 400 may stop.

FIG. 5 is a block diagram of an example system 500 for smart locationdetermination. System 500 may include at least one computing device thatis capable of communicating with at least one remote system. System 500may be similar to system 120 of FIG. 1 or system 300 of FIG. 3, forexample. In the embodiment of FIG. 5, system 500 includes a processor510 and a machine-readable storage medium 520. Although the followingdescriptions refer to a single processor and a single machine-readablestorage medium, the descriptions may also apply to a system withmultiple processors and multiple machine-readable storage mediums. Insuch examples, the instructions may be distributed (e.g., stored) acrossmultiple machine-readable storage mediums and the instructions may bedistributed (e.g., executed by) across multiple processors.

Processor 510 may be one or more central processing units (CPUs),microprocessors, and/or other hardware devices suitable for retrievaland execution of instructions stored in machine-readable storage medium520. In the particular embodiment shown in FIG. 5, processor 510 mayfetch, decode, and execute instructions 522, 524, 526, 528, 530 toperform smart location determination. As an alternative or in additionto retrieving and executing instructions, processor 510 may include oneor more electronic circuits comprising a number of electronic componentsfor performing the functionality of one or more of the instructions inmachine-readable storage medium 520. With respect to the executableinstruction representations (e.g., boxes) described and shown herein, itshould be understood that part or all of the executable instructionsand/or electronic circuits included within one box may, in alternateembodiments, be included in a different box shown in the figures or in adifferent box not shown.

Machine-readable storage medium 520 may be any electronic, magnetic,optical, or other physical storage device that stores executableinstructions. Thus, machine-readable storage medium 520 may be, forexample, Random Access Memory (RAM), an Electrically-ErasableProgrammable Read-Only Memory (EEPROM), a storage drive, an opticaldisc, and the like. Machine-readable storage medium 520 may be disposedwithin system 500, as shown in FIG. 5. In this situation, the executableinstructions may be “installed” on the system 500. Alternatively,machine-readable storage medium 520 may be a portable, external orremote storage medium, for example, that allows system 500 to downloadthe instructions from the portable/external/remote storage medium. Inthis situation, the executable instructions may be part of an“installation package”. As described herein, machine-readable storagemedium 520 may be encoded with executable instructions for smartlocation determination.

Referring to FIG. 5, session information accessing instructions 522,when executed by a processor (e.g., 510), may cause system 500 to accesssession information that details a session of a user system as itconnects to a web technology server. Alleged geographic locationinstructions 524, when executed by a processor (e.g., 510), may causesystem 500 to access or determine an alleged geographic location relatedto an alleged IP address of the user system. Knowledge base accessinginstructions 526, when executed by a processor (e.g., 510), may causesystem 500 to access a knowledge base that includes known common sessioninformation of multiple geographic locations. Comparison instructions528, when executed by a processor (e.g., 510), may cause system 500 tocompare the accessed session information to the knowledge base, andbased on the comparison, determine a geographic location of the usersystem. Geographic location and proxy determination instructions 530,when executed by a processor (e.g., 510), may cause system 500 todetermine that the geographic location is different than the allegedgeographic location, and based on this, determine that a proxy was usedto generate the alleged IP address.

1. A system for smart location determination, the system comprising: asession information accessor to access session information that detailsa session of a user system as it connects to a web technology server; aknowledge base that includes known common session information ofmultiple geographic locations; and a session information comparator tocompare the accessed session information to the knowledge base, andbased on the comparison, determine a geographic location of the usersystem or verify an alleged geographic location.
 2. The system of claim1, wherein the determination of the geographic location includesdetermining which of the multiple geographic locations has associatedcommon session information in the knowledge base that best matches theaccessed session information.
 3. The system of claim 1, wherein thesession information used for the comparison does not include an IP(internet protocol) address.
 4. The system of claim 1, furthercomprising a similarity determinor to, if the session informationcomparator determines a geographic location, determine a similarityrating between common session information of the geographic location andthe accessed session information.
 5. The system of claim 1, furthercomprising a similarity determinor to, if the session informationcomparator verifies an alleged geographic location, determine asimilarity rating between common session information of the allegedgeographic location and the accessed session information.
 6. The systemof claim 1, wherein the accessed session information includes multiplesession parameters, and wherein the accessed session informationincludes an importance rating for at least one of the multiple sessionparameters.
 7. The system of claim 6, wherein the comparison of theaccessed session information to the knowledge base includes consideringthe importance rating for at least one of the multiple sessionparameters.
 8. A method for smart location determination, the methodcomprising: receiving a request from a user system to access a webtechnology; extracting session information from the request that detailsa session of the user system as it sends the request; sending thesession information to a smart system to compare the session informationto known common session information of multiple geographic locations;and receiving, from the smart system, based on the comparison, ageographic location of the user system or a verification of an allegedgeographic location.
 9. The method of claim 8, wherein the sessioninformation does not include an IP (internet protocol) address, andwherein the received geographic location is not based on an IP address.10. The method of claim 8, wherein the request is a web browser request,and wherein the session information is extracted from a user agentstring of the web browser request.
 11. The method of claim 10, whereinthe session information includes both system information of the usersystem and web browser information of the requesting web browser. 12.The method of claim 8, wherein the session information includes multiplesession parameters, and wherein the sending of the session informationincludes sending an importance rating for at least one of the sessionparameters.
 13. The method of claim 8, further comprising receiving asimilarity rating between the sent session information and: commonsession information associated with the geographic location, or commonsession information associated with alleged geographic location.
 14. Amachine-readable storage medium encoded with instructions for smartlocation determination, the instructions executable by a processor of asystem to cause the system to: access session information that details asession of a user system as it connects to a web technology server;access or determine an allege geographic location related to an allegedIP address of the user system; access a knowledge base that includesknown common session information of multiple geographic locations;compare the accessed session information to the knowledge base, andbased on the comparison, determine a geographic location of the usersystem; and determine that the geographic location is different than thealleged geographic location, and based on this, determine that a proxywas used to generate the alleged IP address.
 15. A machine-readablestorage medium of claim 14, wherein the determination that a proxy wasused is further based on previous analysis of other session informationfor other sessions where it was determined for those sessions that thedetermined geographic location was different than the alleged geographiclocation.